Triple
T28129654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beth Jarrett |
E711026
|
entity |
| Predicate | relationshipToBuckJarrett |
P201093
|
FINISHED |
| Object | mother |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: mother | Statement: [Beth Jarrett, relationshipToBuckJarrett, mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToBuckJarrett Context triple: [Beth Jarrett, relationshipToBuckJarrett, mother]
-
A.
relationshipToCalvinJarrett
Indicates the nature or type of relational connection an entity has with Calvin Jarrett.
-
B.
relationshipToGreenBayPackers
Indicates the nature of a person or entity’s connection or association with the Green Bay Packers.
-
C.
relationshipToNFL
Indicates the nature or type of connection an entity has to the National Football League (NFL), such as affiliation, role, or involvement.
-
D.
relationshipToConradJarrett
Indicates the specific type of personal or emotional relationship an entity has with Conrad Jarrett.
-
E.
relationshipToJoeBuck
Indicates the specific familial, social, or professional relationship that one entity has to the person Joe Buck.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ef9b73bd288190a21ae3d6aa14f386 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69ffc7b4c7f88190b6357a44e7f0940f |
completed | May 9, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69ffc755f09c8190995ca00d97336988 |
completed | May 9, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69ffc7b41e688190ad3b86d87c38888e |
completed | May 9, 2026, 11:48 p.m. |
Created at: April 27, 2026, 9:22 p.m.